Blonder et al. (, Global Ecology and Biogeography, 23, 595–609) introduced a new multivariate kernel density estimation (KDE) method to infer Hutchinsonian hypervolumes in the modelling of ecological niches. The authors argued that their KDE method matches or outperforms several methods for estimating hypervolume geometries and for conducting species distribution modelling. Further clarification, however, is appropriate with respect to the assumptions and limitations of KDE as a method for species distribution modelling. Using virtual species and controlled environmental scenarios, we show that KDE both under- and overestimates niche volumes depending on the dimensionality of the dataset and the number of occurrence records considered. We suggest that KDE may be a viable approach when dealing with large sample sizes, limited sampling bias and only a few environmental dimensions.
Bibliographical noteFunding Information:
We thank the editors Richard Field and Antoine Guisan and two anonymous referees for invaluable suggestions that improved this manuscript. H.Q. was supported by the National Natural Science Foundation of China (A New Method to Predict the Species Distributions, 31100390). L.E.E. was supported by the Minnesota Environment and Natural Resources Trust Fund, the Minnesota Aquatic Invasive Species Research Center and the Clean Water Land and Legacy. J.S. was partially supported by NSF grant 1208472. Research interests of the team include invasion ecology, virtual ecology, and the evaluation of ecological niche modeling methods in ecology and epidemiology.
- Ecological space
- Hutchinsonian hypervolumes
- minimum volume ellipsoid
- multivariate kernel density estimation
- virtual species